Information and decision fusion systems for aircraft Structural Health Monitoring

Structural Health Monitoring (SHM) is the process of continuous and autonomous monitoring of the physical condition of a structure by means of sensors. It is a mean of Non-Destructive-Inspection for monitoring and ensuring the structural integrity of aircraft. SHM techniques have been explored to reduce air vehicle maintenance and repair costs while maintaining safety and reliability. This research investigated the benefits provided by developing and applying decision fusion algorithms to SHM systems. These algorithms should provide means for incorporating prior knowledge about the structure to improve the overall SHM system performance. The decisions of classifiers are combined using decision fusion methods to arrive at unified final decisions regarding the state of the monitored structure. The Dempster-Shafer theory of evidence was used for development of the decision-fusion algorithm. The fusion algorithm was implemented in Matlab and was tested on experimental data. The testing and evaluation results showed significant improvement due to fusion.. The testing results reported in this paper compared performance of individual classifier decisions with the decision produced by the decision-fused algorithm.